Sentiment analysis from travellers' reviews using enhanced conjunction rule based approach for feature-specific evaluation of hotels

被引:4
|
作者
Maity, Aranyak [1 ]
Ghosh, Sritama [1 ]
Karfa, Saikat [1 ]
Mukhopadhyay, Moutan [1 ]
Pal, Saurabh [1 ]
Pramanik, Pijush Kanti Dutta [2 ]
机构
[1] Bengal Inst Technol, Dept Comp Sci & Engn, Kolkata 700150, W Bengal, India
[2] Natl Inst Technol, Dept Comp Sci & Engn, Durgapur 713209, W Bengal, India
来源
关键词
Sentiment analysis; Opinion mining; Online review; Aspect-based opinion mining; Aspect-based sentiment analysis; Machine learning; Sentiment orientation; Tourism reviews; Lexicon;
D O I
10.1080/09720510.2020.1799499
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The evolution of the internet has steered an enormous amount of travel reviews of hotels on the web. People referring to these reviews are often overloaded and confused by the sheer amount of information available. Sentiment analysis techniques have been successful in aggregating the reviews, extracting their sentiments and thereby minimizing the information overload. But lacking in specific feature-based sentiment analysis has restricted customers in getting the actual scenario of hotels entirely. This paper presents a prospective design on lexicon-based approach for feature-based sentiment analysis of travel reviews on hotels or resorts. In particular, an enhanced form of conjuncture-based approach is proposed to segregate sentences into relevant clauses, identifying the feature and the sentiment value associated with it. Overall sentiment score for features like food, service, and location of a hotel is being calculated. The experiment results show significantly better accuracy and precision than the conventional text segregation and sentiment analysis methods, namely trigram and conjunction rule based approach.
引用
收藏
页码:983 / 997
页数:15
相关论文
共 50 条
  • [1] A Topic Modeling and Sentiment Analysis Approach for Benchmarking of Hotels Based on Online Reviews
    Suryadi, Dedy
    Imran, Jovanska Arfianda
    INDUSTRIAL ENGINEERING AND MANAGEMENT SYSTEMS, 2022, 21 (04): : 646 - 657
  • [2] An Enhanced Framework for Aspect-Based Sentiment Analysis of Hotels' Reviews: Arabic Reviews Case Study
    Al-Smadi, Mohammad
    Qwasmeh, Omar
    Talafha, Bashar
    Al-Ayyoub, Mahmoud
    Jararweh, Yaser
    Benkhelifa, Elhadj
    2016 11TH INTERNATIONAL CONFERENCE FOR INTERNET TECHNOLOGY AND SECURED TRANSACTIONS (ICITST), 2016, : 98 - 103
  • [3] Feature-based sentiment analysis approach for product reviews
    Liu, L. (xxgccnu@126.com), 1600, Academy Publisher (09):
  • [4] Sentiment Analysis of Amazon Product Reviews Using Hybrid Rule-Based Approach
    Dadhich, Anjali
    Thankachan, Blessy
    SMART SYSTEMS: INNOVATIONS IN COMPUTING (SSIC 2021), 2022, 235 : 173 - 193
  • [5] An enhanced feature-based sentiment analysis approach
    Saeed, Nagwa M. K.
    Helal, Nivin A.
    Badr, Nagwa L.
    Gharib, Tarek F.
    WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, 2020, 10 (02)
  • [6] SAHAR-LSTM: An enhanced Model for Sentiment Analysis of Hotels'Arabic Reviews based on LSTM
    Nejjari, Manal
    Meziane, Abdelouafi
    PROCEEDINGS OF 2020 5TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND ARTIFICIAL INTELLIGENCE: TECHNOLOGIES AND APPLICATIONS (CLOUDTECH'20), 2020, : 67 - 73
  • [7] Improving the accuracy of sentiment analysis using a linguistic rule-based feature selection method in tourism reviews
    Saraswathi N.
    Sasi Rooba T.
    Chakaravarthi S.
    Measurement: Sensors, 2023, 29
  • [8] Sentiment Analysis on User Reviews Through Lexicon and Rule-Based Approach
    Zeb, Sobh
    Qamar, Usman
    Hussain, Faiza
    WEB TECHNOLOGIES AND APPLICATIONS: APWEB 2016 WORKSHOPS, WDMA, GAP, AND SDMA, 2016, 9865 : 55 - 63
  • [9] Aspect Based Sentiment Analysis of Unlabeled Reviews Using Linguistic Rule Based LDA
    Pathik, Nikhlesh
    Shukla, Pragya
    JOURNAL OF CASES ON INFORMATION TECHNOLOGY, 2022, 24 (03)
  • [10] Reduced Feature Based Sentiment Analysis on Movie Reviews Using Key Terms
    Sruthi, S.
    Sheik, Reshma
    John, Ansamma
    2017 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, INFORMATICS, COMMUNICATION AND ENERGY SYSTEMS (SPICES), 2017,